{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T03:24:40.325449Z",
     "start_time": "2020-10-19T03:24:40.034827Z"
    }
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  pytorch, 今から、頑張って！\n",
    "###  そう言ったら、なんでやねん？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T03:48:56.846377Z",
     "start_time": "2020-10-19T03:48:56.767304Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[-1.9515e+07,  4.5726e-41,  2.0319e-43,  0.0000e+00,  1.2603e+27,\n",
       "          3.0845e-41],\n",
       "        [-1.4478e+07,  4.5726e-41, -1.2543e-25,  4.5726e-41, -1.2544e-25,\n",
       "          4.5726e-41],\n",
       "        [-1.2556e-25,  4.5726e-41,  1.3593e-43,  0.0000e+00,  1.2692e+27,\n",
       "          3.0845e-41],\n",
       "        [-1.4478e+07,  4.5726e-41, -1.2562e-25,  4.5726e-41, -1.2562e-25,\n",
       "          4.5726e-41],\n",
       "        [-1.9039e+07,  4.5726e-41, -2.0336e+07,  4.5726e-41, -1.9331e+07,\n",
       "          4.5726e-41]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m= torch.empty(5,6)\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T04:02:07.824209Z",
     "start_time": "2020-10-19T04:02:07.810411Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[1., 1., 1.],\n",
       "        [1., 1., 1.],\n",
       "        [1., 1., 1.]], requires_grad=True)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "afadfsdf=torch.ones(3,3,requires_grad=True)\n",
    "afadfsdf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T04:32:44.549943Z",
     "start_time": "2020-10-19T04:32:44.542717Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[0., 0., 0.],\n",
       "        [0., 0., 0.],\n",
       "        [0., 0., 0.]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l=torch.zeros_like(afadfsdf)\n",
    "l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T04:36:29.450158Z",
     "start_time": "2020-10-19T04:36:29.446702Z"
    }
   },
   "outputs": [],
   "source": [
    "m=np.linspace(0.1,1,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-10-19T04:36:31.915289Z",
     "start_time": "2020-10-19T04:36:31.907546Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   誠にありがとうございます！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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